CAJ | 학술논문

针对蜂窝陶瓷形状不规则、侧面裂纹和侧面缺损细微造成外观质量检测难的问题，将机器视觉应用到侧面缺陷检测中。设计了转盘机构，配合线阵CCD相机采集侧面图像。通过中值滤波消除噪声，通过Canny算子提取边缘；采用领域加权分割法提取缺陷，并获取了侧面二值图像。在此基础上，采用区域生长法标记缺陷区域，选取面积为特征值判定缺陷。研究结果表明，该算法能快速地检测出蜂窝陶瓷侧面缺陷，对不合格样品判定准确，为蜂窝陶瓷外观质量的在线视觉检测奠定了基础。
침대봉와도자형상불규칙、측면렬문화측면결손세미조성외관질량검측난적문제，장궤기시각응용도측면결함검측중。설계료전반궤구，배합선진CCD상궤채집측면도상。통과중치려파소제조성，통과Canny산자제취변연；채용영역가권분할법제취결함，병획취료측면이치도상。재차기출상，채용구역생장법표기결함구역，선취면적위특정치판정결함。연구결과표명，해산법능쾌속지검측출봉와도자측면결함，대불합격양품판정준학，위봉와도자외관질량적재선시각검측전정료기출。
In order to solve the hard detection of such surface quality problems in honeycomb ceramics as irregular shape, subtle surface cracks and tiny side defects, the machine vision was applied to surface defects detection. The side image was captured by a CCD line scan camera with a turntable unit. Median filter was used to remove noise. Canny operator was used to extract edges. Neighboring weighted segmentation was used to extract defects and get the binary image. Region grow was used to mark a detected region. Area characteristic value was used to judge defects. The results indicate that the algorithm can rapidly detect side defects and accurately determine unqualiifed samples;it lays the foundation for surface quality inspection of honeycomb ceramics based on on-line visual.